A 10 Step Approach to Successful BI

A Recommended Course of Action

Raise The Bar
Making better business decisions throughout the enterprise is a perpetual journey. Some additional follow-on initiatives may include:

Grant information dissemination to more people, or increase cross-functional information exchange among more lines of business. The goal is to democratize BI analysis throughout the business.

Improve the speed or timeliness of information delivery. However, not all information needs to be real-time, so align information types with the need for speed.

Implement alert notifications. These notifications are normally delivered in real-time upon a performance metric threshold value being exceeded—and can provide management the opportunity to remedy a performance deviation before it gets out of hand.

Tailor data visualization by roles, and experiment with new information delivery tools, be it new forms of dashboards or tools which permit new methods of slicing and dicing data, possibly by dragging-and-dropping data results with new measures.

Step up to predictive modeling and analysis. This type of analysis uses technology to discover hidden patterns and support 'what-if' scenarios or pro forma modeling. Being able to accurately forecast the effects of new or proposed efforts is a powerful tool in allocating budget and scarce resources among competing alternatives.

Append more unstructured and medios sociales data with existing repositories. Social CRM tools are increasingly acquiring more unstructured customer data. However, for most companies that data remains isolated from their CRM software records.

Moving in the other direction, new social CRM tools and mashups are permitting users to develop analytical scorecards, dashboards, charts and graphs and distribute them to social sites such as blogs, wikis or even Facebook.

Compliment your CRM data, which is largely historical and a lagging indicator of customer behavior, with more current and dynamic data generated from customer surveys, customer loyalty programs and voice of the customer programs. Data from these measures can be used as leading indicators and is generally more telling of the true customer relationship.

Leverage mobility to make insight portable and device agnostic.

Implement training and coaching programs which aid uses in reviewing, interrogating and acting upon the data.

Consider implementing a knowledge management solution in order to centralize and better share policies, training and education materials, instructional procedures, advanced capabilities and best practices.

Check out self service BI solutions, which put powerful but easy to use, browser-based query and reporting tools, interactive graphics and wizard driven creation into the hands of staff. This can be an ideal method to keep up with users growing information demands or relieve under-staffed IT resources.

Conclusion

Information is the fuel that power's intelligent organizations. However, management's traditional use of reviewing static, generic, historical reports which usually only pull data from a single source is no longer sufficient in competitive markets. These reports are designed for passive viewing and do little to proactively advance business initiatives in the shortest cycles possible. What's needed are the strategies and software tools to help decision makers advance from looking in the rear view mirror to instead looking forward through the windshield to see what's ahead.

Business intelligence tools have historically correlated and displayed data as a means to view and analyze what happened by interrogating the data with various measures and dimensions. However, with more powerful BI tools which deliver increased data mining and predictive analytics, more types and volumes of data to increase confidence levels and enhance increased learning, and with new technologies such as cloud and SaaS to simplify and accelerate BI deployments—analytics are no longer just for enterprise companies with deep IT resources.

Executives, managers and staff throughout the organization are responsible to the make the best decisions they can based on the information they have. If the timing, relevancy and insight from that information improves, so will their decisions.
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When pursued strategically, CRM analytics and business intelligence solutions apply more relevant information to decisions, involve more contributors in decision making processes and reach better decisions in less time. If you improve the quality of your decision making processes, you will improve your execution of business objectives.

We first used Microsoft SQL Server analysis services to build out our data warehouse. It's a powerful data warehouse engine, but doesn't offer a good front end OLAP or visualization tool. You can use Excel as the front end but our goals were more strategic than that. Without that front to back seamless integration, our data warehouse turned into a data dump. We finally purchased a true BI platform and have been very happy with the solution.

Umberto Rodriguez

Great article, but as is all too common, your points are largely geared toward sales and service. What about marketing? Its unclear if these CRM analytics, esepcially SAAS BI, apply equally well to marketers.

Chuck Schaeffer

Depending upon the organization, I think marketing can be one of the biggest beneficiaries of CRM analytics. Viewing marketing campaign results and factors, or more likely combinations of factors, that positively or negatively impact response rates is powerful. Examining high volumes of medios sociales data, appended to CRM data, in order to figure out whether time and investments in Twitter and Facebook are paying off with increased sales activities or are just complete time wasters could provide useful for social CRM advocates and skeptics alike.

CEOs and executive teams often grumble that marketing investments do not provide the same level of performance visibility as sales and service operations. As the saying goes, 'about half the marketing investment delivers a payback, I'm just not sure which half.' In addition to correlating investment dollars to payback, analytics can deliver big operational benefits. For example, we know that the timing in delivering an offer is a great predictor of conversion. By correlating the right elements of customer buying behaviors, historical purchase patterns, product upgrades or new releases and even competitor data, marketers can likely quantifiably determine what offers should be delivered to what customers through what channels and when. Marketing successes are based on large numbers of variables. Understanding the correlations and patterns in these factors can certainly lead to improved decision making.

Ross Maynard

We use marketing analytics to understand and project uplift analysis - identifying those customers who only respond if an offer is made, which is different than those customers who accept the offer but would have taken action anyway. By identifying and targeting those customers, we've grown cross sell revenues for each of the last three quarters. We're now about to apply this principal in reverse in an effort to reduce customer churn. We've begun by looking at customers that have cut back on their purchases and are investigating other factors which may be leading indicators to churn. By identifying those at-risk customers who may stay with the company if they're targeted with relevant promotions, financial inducements, retention offers or social communications, we expect to increase customer retention.

Holly Rodgers

All good information, but doesn't seem to be applicable to small business organization who don't have the technical resources for these types of systems. I think we're relegated to the world of excel.

Chuck Schaeffer

Maybe not. It is true that large companies were the early adopters of BI solutions, but that's in large part because they have much larger data volumes and more source applications to contend with, and more IT professionals to tackle these projects. However, SaaS or cloud BI solutions have removed much of the technical complexity associated with procurement, deployment, maintenance and upgrades. And SMB companies have a big advantage using BI solutions in that they are much more agile and can more quickly adapt or implement business strategies learned from business intelligence.

Anonymous

If you can't measure it, you can't manage it.

Lauren Family

The article makes a strong business case for implementing BI, however, all software technology projects have risks and downsides. Can you offer the downsides for most BI projects?

Chuck Schaeffer

Challenges in BI projects often include:

The technical issues in retrieving and consolidating different types of data from disparate data sources. Acquiring non-structured data from social networks and medios sociales destinations is an increasingly common goal that requires a solid data management approach and specialized tools—or risks becoming unwieldy.

Data cleaning and hygiene processes are a discipline that clearly separate over-achievers from under-achievers. In addition to the processes referenced to validate data at the source, having a process and automation tools to remove bogus data, discard unusable data, consolidate redundant data, enrich data and append data based on rule sets will significantly improve data quality, reduce wasted time and effort, empower more efficient analysis and increase information trust and usefulness by the users.

It's been my experience that few organizations measure their information management costs and value. This makes it difficult or impossible to understand what benefits your information assets deliver to the business, whether the value of benefits is growing over time and whether you're getting a ROI. Information management is a material cost, and BI solutions typically lower costs by centralizing data which achieves economies of scale such as fewer computing and human resources to manage and maintain systems as well as increased value such as master data management benefits—and most obviously improved decisions. However, if it's not measured, it's not recognized.

JB Russell

We use Cognos, but it has very mixed reviews and limited adoption because users have to wait on IT to make adjustments. Probably like most companies our IT staff is understaffed. I think the product is fine but would you agree that we've not empowered the users to make their own adjustments?

Chuck Schaeffer

The combination of business and IT staff is essential for successful BI programs. IT staff play an important role in a BI deployment, however, if line of business managers are dependent upon IT staff for editing and manipulating data retrieval, mixing new variables to uncover new patterns or creating new views for new learning, that learning will incur delays. Business analysis is an iterative process and BI solutions must permit users to perform dynamic interrogation of the information on their own. It is essential that any BI solution be configured, modified and updated by the users to maintain learning pace.

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Successful business intelligence deployments are proven to increase overall business performance. In its Operational Intelligence research report, Analyst firm Aberdeen Group reports that companies regarded as best-in-class in using BI achieved 16% annual increase in operating profits compared with only 8% increase for industry average BI users, and 1% decrease for laggards.